A question answering (QA) computing system applies advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering. The key difference between QA technology and document search is that document search takes a keyword query and returns a list of documents, ranked in order of relevance to the query (often based on popularity and page ranking), while QA technology takes a question expressed in natural language, seeks to understand it in much greater detail, and returns a precise answer to the question.
In order to answer a broad array of questions, QA systems rely on vast amounts of up-to-date information. QA Systems need current documents and information in order to more accurately answer questions, especially questions that are time sensitive questions. Currently such technologies are limited by the time it takes considerable to rebuild the information corpora used by the QA system during runtime.